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Main Authors: Voinot, Charlotte, Simon-Tillaux, Noémie, Torrini, Emma, Michiels, Stefan, Sebastien, Bernard, Berenfeld, Clément, Josse, Julie
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2605.20003
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author Voinot, Charlotte
Simon-Tillaux, Noémie
Torrini, Emma
Michiels, Stefan
Sebastien, Bernard
Berenfeld, Clément
Josse, Julie
author_facet Voinot, Charlotte
Simon-Tillaux, Noémie
Torrini, Emma
Michiels, Stefan
Sebastien, Bernard
Berenfeld, Clément
Josse, Julie
contents In this work, we study the estimation of treatment duration effects in observational survival data, where treatment and covariate histories evolve over time and longer observed durations are only attainable among individuals who remain event-free and under follow-up, leading to immortal time bias under naive analyses. The cloning-censoring-weighting (CCW) framework provides a practical approach to emulate target trials of treatment duration strategies, but several methodological aspects remain insufficiently understood. We focus on static treatment duration strategies under two settings of increasing complexity: baseline confounding only, and confounding with time-varying covariates. We formalize the assumptions underlying CCW, with particular emphasis on treatment admissibility, relaxed intervention rules, and the distinction between artificial and natural censoring. We then compare several estimation approaches after cloning and censoring, including inverse probability of censoring weighting (IPCW), the G-formula, and doubly robust estimators, through simulation studies assessing robustness, variability, and sensitivity to censoring model misspecification. Finally, we apply the framework to a Breast Cancer cohort to emulate a target trial comparing 2 versus 5 years of adjuvant tamoxifen in early stage breast cancer. Due to the small number of events and limited support for the 2-year strategy, estimates are associated with substantial uncertainty. These findings highlight both the practical relevance and the limitations of CCW, and underscore the importance of sensitivity analyses in complex longitudinal observational settings.
format Preprint
id arxiv_https___arxiv_org_abs_2605_20003
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Estimating treatment duration effects via clone-censor-weight: a breast cancer case study
Voinot, Charlotte
Simon-Tillaux, Noémie
Torrini, Emma
Michiels, Stefan
Sebastien, Bernard
Berenfeld, Clément
Josse, Julie
Methodology
Applications
In this work, we study the estimation of treatment duration effects in observational survival data, where treatment and covariate histories evolve over time and longer observed durations are only attainable among individuals who remain event-free and under follow-up, leading to immortal time bias under naive analyses. The cloning-censoring-weighting (CCW) framework provides a practical approach to emulate target trials of treatment duration strategies, but several methodological aspects remain insufficiently understood. We focus on static treatment duration strategies under two settings of increasing complexity: baseline confounding only, and confounding with time-varying covariates. We formalize the assumptions underlying CCW, with particular emphasis on treatment admissibility, relaxed intervention rules, and the distinction between artificial and natural censoring. We then compare several estimation approaches after cloning and censoring, including inverse probability of censoring weighting (IPCW), the G-formula, and doubly robust estimators, through simulation studies assessing robustness, variability, and sensitivity to censoring model misspecification. Finally, we apply the framework to a Breast Cancer cohort to emulate a target trial comparing 2 versus 5 years of adjuvant tamoxifen in early stage breast cancer. Due to the small number of events and limited support for the 2-year strategy, estimates are associated with substantial uncertainty. These findings highlight both the practical relevance and the limitations of CCW, and underscore the importance of sensitivity analyses in complex longitudinal observational settings.
title Estimating treatment duration effects via clone-censor-weight: a breast cancer case study
topic Methodology
Applications
url https://arxiv.org/abs/2605.20003